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Fabrication Routes for Ionic Conducting Fiber Strain Sensors

Advanced Engineering Materials, EarlyView.
Ionic conducting fiber strain sensors (ICFSs) offer compliant, textile‐integrable sensing. Thus far, the commercialization of ICFSs has been constrained by fiber fabrication routes. This review provides a fabrication‐centric analysis of ICFSs correlating processing strategies with material properties and scalability.
Leo John Kershaw, Zhanhong Yang, Anne Ladegaard Skov, Magdalena Skowyra   +3 more
wiley   +1 more source

Morphology, Transport, and Dynamics of Protein Adsorption in Open‐Cell Metal Foam

Advanced Engineering Materials, EarlyView.
Stainless steel (SS) open‐cell foams are shown to adsorb more protein per unit area than previously reported 316L SS and chromium oxide surfaces under static and flow conditions. An integrated approach combining 3D pore imaging, flow simulation, and protein adsorption experiments characterizes the foam’s performance.
Chinmaya Prerana Inguva, Joseph Lavoie, Afsaneh Rabiei   +2 more
wiley   +1 more source

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SEGMENTATION OF SPINAL SUBARACHNOID LUMEN WITH 3D ATTENTION U-NET

Journal of Mechanics in Medicine and Biology, 2023
Phase Contrast Magnetic Resonance Image (PC-MRI) is an emerging noninvasive technique that contains pulsatile information by measuring the parameters of cerebrospinal fluid (CSF) flow. As CSF flow quantities are measured from the selected region on the images, the accuracy in the identification of the interested region is the most essential, and the ...
Keleş, A., Algın, Oktay, Özışık Akdemir, P., Şen, B., Çelebi, F. V.   +4 more
openaire   +3 more sources

Blood Vessel Segmentation Based on the 3D Residual U-Net

International Journal of Pattern Recognition and Artificial Intelligence, 2021
In this paper, we propose blood vessel segmentation based on the 3D residual U-Net method. First, we integrate the residual block structure into the 3D U-Net. By exploring the influence of adding residual blocks at different positions in the 3D U-Net, we establish a novel and effective 3D residual U-Net. In addition, to address the challenges of pixel
Mulin Xin, Jing Wen, Yi Wang 0074, Wei Yu, Bin Fang 0001, Jun Hu, Yongmei Xu, Chunhong Linghu   +7 more
openaire   +2 more sources

3D Neuron Segmentation Based on 3D DSAC U-Net

2020 8th International Conference on Digital Home (ICDH), 2020
In the brain, the nerve fibers of adjacent neurons are intertwined. If the three-dimensional neuron image is directly tracked and reconstructed, it is easy to be interfered by nerve fibers and other noises. Therefore, the basic work of reconstructing or tracing 3D neuron structure is to segment the target neuron from neuron images containing nerve ...
Wenbo Tang, Huiwen Huang, Yongyi Gong, Fang Li, Ji Li, Xiaonan Luo   +5 more
openaire   +1 more source

On Improving 3D U-net Architecture

Proceedings of the 14th International Conference on Software Technologies, 2019
This paper presents a review of various techniques for improving the performance of neural networks on segmentation task using 3D convolutions and voxel grids – we provide comparison of network with and without max pooling, weighting, masking out the segmentation results, and oversampling results for imbalanced training dataset. We also present changes
Roman Janovský, David Sedlácek, Jirí Zára   +2 more
openaire   +2 more sources

Choroid Plexus Segmentation Using Optimized 3D U-Net

2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 2020
The choroid plexus is the primary organ that secretes the cerebrospinal fluid. Its structure and function may be associated with the brain drainage pathway and the clearance of amyloid-beta in Alzheimer's Disease. However, choroid plexus segmentation methods have rarely been studied.
Li Zhao 0001, Xue Feng 0001, Craig H. Meyer, David C. Alsop   +3 more
openaire   +1 more source

Comparison of tissue segmentation performance between 2D U-Net and 3D U-Net on brain MR Images

2021 International Conference on Electronics, Information, and Communication (ICEIC), 2021
In this paper, we compare the tissue segmentation performance of the 2D U-Net and 3D U-Net in brain MR images including Alzheimer's disease. The Open Access Series of Imaging Studies dataset used in this experiment consists of a cross-sectional collection of 416 subjects aged 18 to 96. The final segmentations were classified into 4 classes: background,
Boyeong Woo, Myungeun Lee
openaire   +1 more source

3D U-Net for Brain Tumour Segmentation

2019
In this work, we present a 3D Convolutional Neural Network (CNN) for brain tumour segmentation from Multimodal brain MR volumes. The network is a modified version of the popular 3D U-net [13] architecture, which takes as input multi-modal brain MR volumes, processes them at multiple scales, and generates a full resolution multi-class tumour ...
Raghav Mehta, Tal Arbel
openaire   +2 more sources

Brain Tumor Segmentation Based on 3D Residual U-Net

2020
We propose a deep learning based approach for automatic brain tumor segmentation utilizing a three-dimensional U-Net extended by residual connections. In this work, we did not incorporate architectural modifications to the existing 3D U-Net, but rather evaluated different training strategies for potential improvement of performance.
Megh Bhalerao, Siddhesh P. Thakur
openaire   +1 more source